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Wearable Sensors for Reliable Fall Detection
Chen, J.   Karric Kwong   Chang, D.   Luk, J.   Bajcsy, R.  
Dept. of Electr. Eng., California Univ., Berkeley, CA;

This paper appears in: Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Publication Date: 17-18 Jan. 2006
On page(s): 3551-3554
Location: Shanghai,
ISBN: 0-7803-8741-4
INSPEC Accession Number: 9154128
Digital Object Identifier: 10.1109/IEMBS.2005.1617246
Current Version Published: 2006-04-10

Abstract
Unintentional falls are a common cause of severe injury in the elderly population. By introducing small, non-invasive sensor motes in conjunction with a wireless network, the Ivy Project aims to provide a path towards more independent living for the elderly. Using a small device worn on the waist and a network of fixed motes in the home environment, we can detect the occurrence of a fall and the location of the victim. Low-cost and low-power MEMS accelerometers are used to detect the fall while RF signal strength is used to locate the person

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